Suitable albumin concentrations for enhanced drug oxidation activities mediated by human liver microsomal cytochrome P450 2C9 and other forms predicted with unbound fractions and partition/distribution coefficients of model substrates

Abstract

1. Albumin has reportedly enhanced cytochrome P450 (P450)-mediated drug oxidation rates in human liver microsomes. Consequently, measurements of clearances and fractions metabolized could vary depending on the experimental albumin concentrations used.

2. In this study, the oxidation rates of diclofenac and warfarin by human liver microsomes were significantly enhanced in the presence of 0.10% (w/v) bovine serum albumin, whereas those of tolbutamide and phenytoin required 1.0% and 2.0% of albumin for significant enhancement. Values of the fractions metabolized by P450 2C9 for four substrates did not markedly change in the presence of albumin at the above-mentioned concentrations.

3. The oxidation rates of bupropion, omeprazole, chlorzoxazone and phenacetin in human liver microsomes were reportedly enhanced by 0.5%, 1%, 2% and 2% of albumin, respectively. Analysis of reported intrinsic clearance values and suitable albumin concentrations for the currently analyzed substrates and the reported substrates revealed an inverse correlation, with warfarin as an outlier.

4. Suitable albumin concentrations were multivariately correlated with physicochemical properties, that is, the plasma unbound fractions, octanol–water partition coefficient and acid dissociation constant (r = 0.98, p<.0001, n = 10). Therefore, multiple physicochemical properties may be determinants of suitable albumin concentrations for substrate oxidations in human liver microsomes.

Keywords:

• Diclofenac
• warfarin
• acid dissociation constant
• octanol–water partition coefficient
• CYP 2C9

Acknowledgements

The authors thank Drs. Makiko Shimizu, Yusuke Kamiya and Masato Kitajima for their technical help and we thank David Smallbones for his advice on English language usage.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This study was funded by the METI Artificial Intelligence–Substances Hazardous Integrated Prediction System Project, Japan.